A very interesting paper that proposes biomarkers as important ‘end points’ in clinical trials for rare disease drugs. And why is this important for genetic skeletal disease…..?
There are currently no effective diagnostic and prognostic biomarkers of early stage cartilage degradation for both common and rare skeletal diseases. Diagnosis of arthritis is currently based on imaging techniques such a radiographs performed well after the onset of symptoms such as pain and stiffness. Early and non-invasive markers of cartilage degeneration will provide an evidence-base for appropriate clinical management regimes.
Furthermore, biomarkers are also a vital requirement in clinical trials. Recent advances in understanding disease mechanisms has led to clinical trails for two rare skeletal disease; hypophosphatasia and achondroplasia. However, lack of a suitable biomarker has had a negative impact on defining end-points for these trials.
An interesting historical breakdown of gene identification for rare skeletal diseases in the 25 years from 1988 to 2011.
What becomes apparent is that technology clearly drives the process of gene discovery and that there are ‘peaks in discovery’ that are closely aligned with ‘new’ technologies.
The availability of highly informative microsatelllite markers, which could even be assembled into panels for multiplexing (pioneered by Jim Weber in Marshfield Wisconsin), heralded the first increase in gene identification starting in the early to mid 1990’s.
This approach was massively enhanced with the publication of the Human Genome, which allowed a rapid transition from candidate region to candidate genes. For example, in our multiple epiphyseal dysplasia (MED) study of 2001 we went from a linked candidate region of 60cM to three candidate genes; TIMP3, SDC1 and MATN3 – we chose wisely Chapman et al 01.
High throughput SNP analysis aided in the identification of numerous genes responsible for recessive skeletal diseases through homozygosity mapping.
Most recently arrays and next generation sequencing has completely revolutionised disease gene discovery in rare (skeletal) diseases.
A super example of gene discovery using exome sequencing comes from Andreas Zankl, Matt Brown and colleagues.
In summary, exome sequencing of both parents and the affected siblings in this family identified:-
90% of targeted nucleotides had coverage of >four-fold
79% of targeted nucleotides had coverage >ten-fold
~15,000 SNPs identified following bioinformatic filtering!
>96% SNPs were reported in the recent dbSNP database and were therefore excluded from further analysis as unlikely to cause this rare disease.
Following the functional annotation of the remaining novel SNPs, focused analyses on a set of 483 unique novel coding non-synonymous SNPs that were detected in at least one sample.
Careful selection of ‘mode of inheritance’ allowed the identification of just four candidate genes.
In all but one gene the detected missense mutations were predicted to be tolerated in terms of effect upon protein function.
The single remaining candidate gene carried two novel alleles :-
One creating a premature stop codon.
One causing a missense mutation predicted to have a damaging effect on protein function.
POP1 a strong candidate for the disease-causing gene in this family.
Needless to say that this story made a great 2nd year undergraduate lecture Exome Lecture.